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Supporting Online Material Supplementary Information for Climate drives the geography of marine consumption by changing predator communities Matthew A. Whalen, Ross D.B. Whippo, John J. Stachowicz, Paul H. York, Erin Aiello, Teresa Alcoverro, Camilla Bertolini, Lisandro Benedetti-Cecchi, Midoli Bresch, Fabio Bulleri, Paul E. Carnell, Stéphanie Cimon, Rod M. Connolly, Mathieu Cusson, Meredith S. Diskin, Elrika D'Souza, Augusto A.V. Flores, F. Joel Fodrie, Aaron W.E. Galloway, Leo C. Gaskins, Olivia J. Graham, Torrance C. Hanley, Christopher J. Henderson, Clara M. Hereu, Margot Hessing-Lewis, Kevin A. Hovel, Brent B. Hughes, A. Randall Hughes, Kristin M. Hultgren, Holger Jänes, Dean S. Janiak, Lane N. Johnston, Pablo Jorgensen, Brendan P. Kelaher, Claudia Kruschel, Brendan S. Lanham, Kun-Seop Lee, Jonathan S. Lefcheck, Enrique Lozano-Álvarez, Peter I. Macreadie, Zachary L. Monteith, Nessa E. O'Connor, Andrew D. Olds, Jennifer K. O'Leary, Christopher J. Patrick, Oscar Pino, Alistair G.B. Poore, Michael A. Rasheed, Wendel W. Raymond, Katrin Reiss, O. Kennedy Rhoades, Max T. Robinson, Paige G. Ross, Francesca Rossi, Thomas A Schlacher, Janina Seemann, Brian R. Silliman, Delbert L. Smee, Martin Thiel, Richard K.F. Unsworth, Brigitta I. van Tussenbroek, Adriana Vergés, Mallarie E. Yeager, Bree K. Yednock, Shelby L. Ziegler, J. Emmett Duffy Matthew Adam Whalen Email: [email protected] This PDF file includes: Figures S1 to S7 Tables S1 to S3 Legend for Move S1 SI References Other supplementary materials for this manuscript include the following: Movies S1 1 Fig. S1. Patterns of consumer (A) species richness, (B) diversity expressed as the number of equally abundant species needed to produce observed values of Hurlburt’s probability of interspecific encounter (1), (C) density, and (E) biomass across mean annual sea surface temperature. Lines are LOESS curves (with shaded 95% confidence intervals) independently fitted within each habitat (green=seagrass, gold=unvegetated sediments). Note that density and biomass (C,D) are shown on a log scale. 2 Fig. S2. Relationships between consumption rate and (A) latitude and (B) mean annual sea surface temperature (SST) along the coastlines for which we have sufficient data to test for the presence and shape of latitudinal gradients. Solid lines show logistic regressions with quadratic terms for Latitude or SST, and dashed lines show logistic regressions with linear predictor terms only. Note that while the Eastern North Pacific follows trends in the Southern Hemisphere well, we do not discuss this case specifically in the text because we lack sufficient sampling towards warmer, low latitude environments. 3 Fig. S3. Bivariate relationships among consumption rate and explanatory variables. (A) Water temperature measured at the time of feedings assays tended to exceed long-term average sea surface temperature, as most studies took place during the summer. Differences between mean annual and measured water temperature decreased toward the warmest sites, but variance was highest between 15 and 25 . The red line shows predictions from local regression (LOESS) and the black line is the 1:1 line. (B) Correlations between mean annual SST, the proportion of active foraging consumer taxa, consumer℃ functional richness measured from all scored traits, an index of multivariate consumer composition (PCoA axis 1 from Fig. 2), the abundance of consumers (log-transformed) identified using ordination constrained to consumption rates, and consumption rates (logit-transformed). Red lines within the scatterplots below the diagonal show predictions from LOESS, panels along the diagonal show the frequency and density of each variable, and numbers above the diagonal show Spearman rank correlation coefficients. 4 Fig. S4. Relationships between consumption rate and community-level weighted trait means for six traits relevant to feeding and locomotion. Traits means are based on presence-absence data of consumers from seines and videos for all traits except length, which we weighted by abundance and restricted to seining data. Points represent mean consumption rate for communities in each site and habitat combination. The x-axis in the upper-left panel reflects whether the dominant consumer is an active swimming forager (1) or not (0). Body size in total length for fish and carapace width for crabs. 5 Fig. S5. Distribution of presences (1) and absences (0) for selected taxonomic families across latitude. Solid black lines are predicted values from a quadratic logistic model and the dotted lines are local regression (LOESS) curves. Shown are the 13 families with the strongest positive correlation with consumption, the 6 families with strongest negative correlation with consumption rate, and wrasses (Labridae). 6 Fig. S6. Consumption rate estimates within each habitat at every site. Filled symbols show rate estimates from individual assays in seagrass (green) and unvegetated (gold) habitats and are semi-transparent to show overlapping estimates. Open black symbols show the mean consumption rate in each habitat. Note the different scale of the y-axis in each panel, which span the range of observed consumption rates at each site. 7 FL Korea Croatia QLD1 NSW1 Fig. S7. Histogram of parameter estimates from linear models of consumption rate as a function of habitat (seagrass vs. unvegetated sediments), independently-fitted for each site. Estimates above zero mean that consumption rate was higher in seagrass than unvegetated sediments. Sites in the extreme bins of the histogram are labelled. At NSW1, for example, all squid bait were consumed after one hour in seagrass, while just over 40% were consumed in one hour in unvegetated sediments, representing a change in consumption rate of nearly 0.6 hr-1. Estimates for 20 of 38 within-site comparisons fell within the range -0.02 to 0.02. 8 Table S1. Correlations between the presence of predator families and consumption rate based on canonical correspondence analysis of predator taxonomic composition. Correlation is derived from the first axis of the constrained ordination of family composition as a function of consumption rate. Also displayed are the number of morphospecies in each family, the number of sites in our dataset where each family was observed, and patterns of presence and absence in seagrass and unvegetated habitats. Families marked with an asterisk were observed to attack or remove the squid bait from at least one of the 10 sites with video data (Table S3). Family Morphospecies Sites Seagrass Unvegetated Correlation Sparidae* 14 10 1 1 0.41 Hemiramphidae* 9 7 1 1 0.29 Mugilidae 8 9 1 1 0.25 Gerreidae 6 10 1 1 0.25 Ambassidae 3 3 1 1 0.24 Sillaginidae 3 6 1 1 0.23 Terapontidae 3 5 1 1 0.23 Tetraodontidae* 10 9 1 1 0.19 Monacanthidae 6 7 1 1 0.19 Tetrarogidae 2 4 1 1 0.19 Haemulidae* 6 5 1 1 0.12 Atherinidae 6 8 1 1 0.12 Gobiidae 26 18 1 1 0.10 Monodactylidae 1 2 1 0 0.09 Penaeidae 5 5 1 1 0.09 Mullidae 4 5 1 1 0.09 Lethrinidae* 6 3 1 1 0.08 Siganidae 4 3 1 1 0.08 Batrachoididae 1 1 1 1 0.08 Carcharhinidae* 1 1 1 1 0.07 Nemipteridae* 3 1 1 1 0.07 Sphyraenidae 3 5 1 1 0.06 Soleidae 2 2 0 1 0.06 Aulostomidae 1 1 1 0 0.06 Pseudomugilidae 1 1 1 0 0.06 Eleotridae 1 1 1 0 0.06 Muraenidae* 1 1 1 0 0.05 Palaemonidae 7 7 1 1 0.04 Serranidae* 7 6 1 1 0.04 Synodontidae 3 3 1 1 0.04 Caesionidae* 1 1 1 0 0.04 Pomacentridae* 2 2 1 1 0.04 Fundulidae 6 4 1 1 0.03 Kyphosidae 2 2 1 1 0.03 Labridae* 25 10 1 1 0.03 Diodontidae 2 3 1 0 0.03 Ariidae* 1 1 1 1 0.03 9 Arripidae 1 1 0 1 0.03 Chaetodontidae 1 1 0 1 0.03 Echeneidae 1 1 0 1 0.03 Fistulariidae 1 1 1 0 0.02 Trichechidae 1 1 0 1 0.02 Acanthuridae 3 2 1 1 0.02 Callionymidae 3 3 1 1 0.02 Loliginidae 2 2 1 1 0.02 Sepiidae 2 2 1 1 0.01 Sciaenidae 7 6 1 1 0.01 Platycephalidae 3 4 1 1 0.01 Blenniidae* 9 9 1 1 0.01 Scyliorhinidae* 1 1 1 0 0.01 Lutjanidae* 10 5 1 1 0.01 Portunidae 7 9 1 1 0.00 Elopidae 1 1 0 1 -0.01 Panopeidae 1 1 0 1 -0.01 Lysmatidae 1 1 1 0 -0.01 Rhinobatidae 1 1 1 0 -0.01 Acropomatidae 1 1 1 1 -0.01 Lateolabracidae 1 1 1 1 -0.01 Triglidae 2 2 1 1 -0.01 Urotrygonidae* 1 1 1 0 -0.01 Gobiesocidae 1 1 1 0 -0.01 Carangidae* 8 4 1 1 -0.01 Hippolytidae 1 1 1 1 -0.01 Trachinidae 1 1 0 1 -0.01 Rhombosoleidae 1 1 0 1 -0.01 Ovalipidae 1 1 0 1 -0.01 Osmeridae 1 1 0 1 -0.01 Cheilodactylidae 1 1 1 0 -0.01 Liparidae 1 1 1 0 -0.01 Stichaeidae 1 1 1 0 -0.01 Processidae 1 1 1 1 -0.01 Hexagrammidae 4 2 1 1 -0.02 Balistidae 2 1 1 1 -0.03 Albulidae 1 1 1 1 -0.03 Varunidae 1 3 1 1 -0.03 Cyprinodontidae 2 2 1 1 -0.03 Moronidae 1 2 1 1 -0.03 Paguridae 1 1 1 1 -0.03 Phycidae 1 1 1 1 -0.03 Salmonidae 2 2 0 1 -0.03 Cyclopteridae 1 2 1 0 -0.03 Salangidae 1 1 1 1 -0.03 10 Paralichthyidae 9 9 1 1 -0.04 Belonidae 2 3 1 1 -0.04 Engraulidae 3 3 1 1 -0.04 Epialtidae 2 3 1 0 -0.04 Aulorhynchidae 1 3 1 0 -0.04 Agonidae 2 2 1 1 -0.04 Ammodytidae 3 3 1 1 -0.05 Sebastidae 4 3 1 1 -0.05 Clinidae 2 3 1 1 -0.06 Gadidae 7 4 1 1 -0.06 Ostraciidae* 2 3 1 1 -0.06 Crangonidae 3 4 1 1 -0.07 Gasterosteidae 8 5 1 1 -0.07 Pholidae 6 6 1 1 -0.09 Clupeidae 9 7 1 1 -0.11 Syngnathidae 14 18 1 1 -0.12 Atherinopsidae 6 11 1 1 -0.15 Cancridae* 7 7 1 1 -0.16 Pleuronectidae 9 8 1 1 -0.16 Embiotocidae 13 8 1 1 -0.17 Cottidae 16 12 1 1 -0.18 11 Table S2.
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